N6-Methyladenosine-Related lncRNAs As Potential Biomarkers For Predicting The Prognoses And Immune Responses In Patients With Cervical Cancer

Abstract

\n Background: Several recent studies have confirmed to us the epigenetic regulation of the immune response. However, the potential role of RNA N6-methyladenosine (m6A) modifications in cervical cancer and its tumor microenvironment (TME) cell infiltration remains unclear.Results: We evaluated and analyzed m6A modification patterns in 307 cervical cancer samples from The Cancer Genome Atlas (TCGA) dataset based on 13 m6A regulators. Pearson correlation analysis was used to identify lncRNAs associated with m6A, followed by univariate Cox regression analysis to screen their prognostic role in cervical cancer patients. We also correlated TME cell infiltration characteristics with modification patterns. We screened six m6A-associated lncRNAs as prognostic lncRNAs and established the prognostic profile of m6A-associated lncRNAs by least absolute shrinkage and choice of operator (LASSO) Cox regression. The corresponding risk scores of patients were derived based on their prognostic features, and the correlation between this feature model and disease prognosis was analyzed. The prognostic model constructed based on the TCGA-CESC (The Cancer Genome Cervical squamous cell carcinoma and endocervical adenocarcinoma) dataset showed strong prognostic power in the stratified analysis and was confirmed as an independent prognostic indicator for predicting overall survival of patients with CESC. Principal component analysis showed that low- and high-risk subgroups had significant m6A status. Enrichment analysis showed that biological processes, pathways, and markers associated with malignancy were more common in the high-risk subgroup. Risk scores were strongly correlated with tumor grade. ECM receptor interaction, pathways in cancer were enriched in cluster 2 while oxidative phosphorylation and other biological processes in cluster 1. The expression of immune checkpoint molecules including PD-1 (programmed death 1) and PD-L1 (programmed death ligand 1) was significantly increased in the high-risk subgroup, suggesting that this prognostic model could be a predictor of immunotherapy.Conclusions: This study reveals that m6A modifications play an integral role in the diversity and complexity of TME formation. Assessing the m6A modification patterns of individual tumors will help improve our understanding of TME infiltration characteristics and thus guide immunotherapy more effectively. We also developed an independent prognostic model based on m6A-associated lncRNA as a predictor of overall survival, which can also be used as a predictor of immunotherapy.